• Corpus ID: 46895963

CascadeCNN: Pushing the performance limits of quantisation

@article{Kouris2018CascadeCNNPT,
  title={CascadeCNN: Pushing the performance limits of quantisation},
  author={Alexandros Kouris and Stylianos I. Venieris and Christos-Savvas Bouganis},
  journal={ArXiv},
  year={2018},
  volume={abs/1805.08743}
}
This work presents CascadeCNN, an automated toolflow that pushes the quantisation limits of any given CNN model, to perform high-throughput inference by exploiting the computation time-accuracy trade-off. Without the need for retraining, a two-stage architecture tailored for any given FPGA device is generated, consisting of a low- and a high-precision unit. A confidence evaluation unit is employed between them to identify misclassified cases at run time and forward them to the high-precision… 

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